Senior Machine Learning Engineer
Tasks
- Architect ML systems for latency throughput scalability
- Build data pipelines for ML workflows
- Collaborate with applied research on production constraints
- Define model monitoring and reliability standards
- Design scalable ML systems for batch use cases
- Establish model lifecycle practices versioning rollback retraining
- Integrate models into pipelines and services
- Mentor engineers on ML engineering and system design best practices
- Optimize cost performance and efficiency
- Process data with Spark
- Productionize machine learning models
- Serve ML models for inference
Perks/Benefits
Skills/Tech-stack
Apache Spark | Data Pipelines | Distributed Computing | Feature Engineering | MLOps | Machine Learning | Model Monitoring | Model Serving | Model retraining | Model versioning | PySpark | Python | SQL
Education
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